C. L. Lawson and R. J. Hanson, Solving Least Squares Problems. Society for Industrial and Applied Mathematics (SIAM), 1995.  Home/Search Document Not in Database Summary Related Articles Check |
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A State Model for the Software Test Process with.. - Cangussu, DeCarlo.. (2001) (Correct)
..... 7 7 7 ; Z = 6 6 6 . 7 7 7 5 and x 0 = r(0) r(0) We know that Z = Px 0 and we can compute x 0 = P L Z. However, this results in a high initial velocity and penalizes the computation of r(0) The problem is solved by applying a weighted least squares approach [8]: Z = PWx 0 ) x 0 = P W ) PW ) PW ) Z (10) where W = w r0 0 0 w v0 is the weight matrix. The weights w r0 and w v0 are usually de ned as [8] where is the standard deviation computed from the observed data for r and from the estimates of r. In the case of the STP, ....
....a high initial velocity and penalizes the computation of r(0) The problem is solved by applying a weighted least squares approach [8] Z = PWx 0 ) x 0 = P W ) PW ) PW ) Z (10) where W = w r0 0 0 w v0 is the weight matrix. The weights w r0 and w v0 are usually de ned as [8] where is the standard deviation computed from the observed data for r and from the estimates of r. In the case of the STP, due to the exponential decay will increase as more data becomes available. This will make the value of the weights decrease when the opposite behavior is expected. To ....
C. L. Lawson and R. J. Hanson, Solving Least Squares Problems. Society for Industrial and Applied Mathematics (SIAM), 1995.
A Spline Approximation Of A Large Set Of Points - Kostkova, Halir (2000) (1 citation) (Correct)
....the small number of intervals (5 10) is sufficient. 3.2 Spline Coefficients After the number of intervals is known, the coefficients of the appropriate spline function are estimated by the approximation of the points with respect to the function smoothness. The standard least squares method [Lawso95] is chosen for computing these coefficients, what formulated the following task: min c kAc Gamma bk 2 under Bc = 0 : 1) The matrix A expresses the approximation of the points, the matrix B represents the smoothness conditions and c is the vector of spline coefficients. In the following ....
Ch. L. Lawson and R. J. Hanson. Solving Least Squares Problems. Number 15 in Classics in Applied Mathematics. Society for Industrial and Applied Mathematics, 1995.
Row-Wise Backward Stable Elimination Methods for the Equality.. - Cox, Higham (2000) Self-citation (Squares) (Correct)
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Charles L. Lawson and Richard J. Hanson. Solving Least Squares Problems. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 1995.
Stability of Householder QR Factorization for Weighted Least.. - Cox, Higham (1997) (5 citations) Self-citation (Squares) (Correct)
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Charles L. Lawson and Richard J. Hanson. Solving Least Squares Problems. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 1995.
Sensitivity Analysis of a State Variable Model - Of The Software (Correct)
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C. L. Lawson and R. J. Hanson, Solving Least Squares Problems. Society for Industrial and Applied Mathematics (SIAM), 1995.
Notes on Accuracy and Stability of Algorithms in Numerical Linear .. - Higham (1998) (Correct)
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Charles L. Lawson and Richard J. Hanson. Solving Least Squares Problems. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 1995.
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